by Max Pechyonkin – 8 min read
Traditional ensembling combines several different models and makes them predict on the same input. Then some way of averaging is used to determine the final prediction of the ensemble.
The 4 Recommendation Engines That Can Predict Your Movie Tastes
by James Le – 18 min read
Have you ever had to answer this question at least once when you came home from work? As for me – yes, and more than once. From Netflix to Hulu, the need to build robust movie recommendation systems is extremely important given the huge demand for personalized content of modern consumers.
Hyper-parameters in Action! Introducing DeepReplay
by Daniel Godoy – 8 min read
In my previous post, I invited you to wonder what exactly is going on under the hood when you train a neural network. Then I investigated the role of activation functions, illustrating the effect they have on the _feature space_using plots and animations.
Automold- specialized augmentation library for Autonomous vehicles
by ujjwal saxena – 5 min read
It was not long into Udacity’s Self driving car nano-degree course when I realized that besides normally followed augmentation techniques, self-driven cars also require specialized augmentation. A self driven car is one of the most complex challenges of AI and also different from other challenges in many aspects.
Web Scraping, Regular Expressions, and Data Visualization: Doing it all in Python
by William Koehrsen – 7 min read
As with most interesting projects, this one started with a simple question asked half-seriously: how much tuition do I pay for five minutes of my college president’s time? After a chance pleasant discussion with the president of my school (CWRU), I wondered just how much my conversation had cost me.
How to Ace the In Person Data Science Interview
by Kristen Kehrer – 7 min read
I’ve written previously about my recent job hunt, but this article is solely devoted to the in-person interview. That full-day, try to razzle-dazzle em’, cross your fingers and hope you’re well prepared for what gets thrown at you.
My First Data Scientist Internship
by Admond Lee – 7 min read
At the point of writing, it was the day before the last day of my Data Scientist internship at Quantum Inventions. And now, sitting before the laptop screen, reflecting on the learning journey for the past few months is nothing but truthfully hard yet fulfilling.
Why Machine Learning on The Edge?
by Neil Tan – 5 min read
Software engineering can be fun, especially when working toward a common goal with like-minded people. Ever since we started the uTensor project, a microcontrollers (MCUs) artificial intelligent framework, many have asked us: why bother with edge computing on MCUs? Aren’t the cloud and application processors enough for building IoT systems? Thoughtful questions, indeed.
Light on Math Machine Learning: Intuitive Guide to Understanding KL Divergence
by Thushan Ganegedara – 10 min read
I’m starting a new series of blog articles following a beginner friendly approach to understanding some of the challenging concepts in machine learning. To start with, we will start with KL divergence.